loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
9th International Parallel Processing Symposium
Symbolic range propagation
Santa Barbara, CA
April 25-April 28
ISBN: 0-8186-7074-6
W. Blume, Center for Supercomput. Res. & Dev., Illinois Univ., Urbana, IL, USA
R. Eigenmann, Center for Supercomput. Res. & Dev., Illinois Univ., Urbana, IL, USA
Many analyses and transformations in a parallelizing compiler can benefit from the ability to compare arbitrary symbolic expressions. In this paper, we describe how one can compare expressions by using symbolic ranges of variables. A range is a lower and upper bound on a variable. We describe how these ranges can be efficiently computed from the program test. Symbolic range propagation has been implemented in Polaris, a parallelizing compiler being developed at the University of Illinois, and is used for symbolic dependence testing, detection of zero-trip loops, determining array sections possibly referenced by an access, and loop iteration-count estimation.
Index Terms:
parallelising compilers; program compilers; symbol manipulation; symbolic range propagation; transformations; parallelizing compiler; arbitrary symbolic expressions; upper bound; lower bound; program test; Polaris; zero-trip loops; array sections; loop iteration-count estimation
Citation:
W. Blume, R. Eigenmann, "Symbolic range propagation," ipps, pp.357, 9th International Parallel Processing Symposium, 1995
Usage of this product signifies your acceptance of the Terms of Use.